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Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Nemotron 3.5 Super VL (Free)NVIDIARemove
  2. GLM 5.3 FlashZ.AIRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

nemotron-3.5-super-vl:free vs glm-5.3-flash vs perceptron-mk1.5 vs muse-wonder
AttributeNemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:freeGLM 5.3 Flashglm-5.3-flashPerceptron Mk1.5perceptron-mk1.5Muse Wondermuse-wonder
Pricing
Input$0 / 1M$0.075 / 1M$0.15 / 1M$4.00 / 1M
Output$0 / 1M$0.25 / 1M$1.50 / 1M$20.00 / 1M
Cache Write$0 / 1M———
Cache Read$0 / 1M$0.075 / 1M$0.15 / 1M$4.00 / 1M
Cache Write (5m)—$0.075 / 1M$0.15 / 1M$4.00 / 1M
Cache Write (1h)—$0.075 / 1M$0.15 / 1M$4.00 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M36.9K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesYesYes
Catalogue
ProviderNVIDIAZ.AIPerceptronMeta
Categorychatchatchatchat
Charge typeFreePay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
SummaryNVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.